Mohammad Heidari-Kapourchali

A new algorithm for reliability evaluation of radial distribution networks

This paper proposes a new algorithm for reliability evaluation of complex radial distribution networks. The proposed algorithm is based on failure mode and effect analysis (FMEA) method. The paper talks about the definition of network topology using a matrix which is modified and new matrices are derived. These matrices are used for evaluation of load point reliability indices. The rows and columns of these matrices correspond to branches and buses of the network respectively. Each element of these matrices attest a specific relation between a faulted branch and the network bus. The above mentioned salient features make the whole algorithm straight forward to implement in a real distribution system. Thus, the results obtained from this method are verified with the Bus 2 of RBTS.

Modeling of uncertainty in distribution network reconfiguration using Gaussian Quadrature based approximation method

Distribution feeder reconfiguration is a cost-effective scheme to improve the system operating condition. Making decisions on the status of switches along the feeder with high penetration of renewable resources requires a tractable and accurate input data analysis. This paper presents a method using Gaussian quadrature to approximate probability distribution function of input variables with a probability mass function. The method is applied to Weibull wind speed and Beta solar irradiance probability distribution functions. These approximated input variables are fed into an energy loss minimization problem to find the best configuration of 33-bus Baran test system in a typical summer day. Group search optimizer, a swarm intelligence optimization method, is applied to solve the problem. In order to analyze the accuracy and efficiency of the proposed method, Monte Carlo simulation and two other approximation methods- bracket midpoint and bracket mean- are used for comparison. Results show the superiority of the method in computational time and its adequate precision.

Reliability analysis of cyber-enabled power distribution system using sequential Monte-Carlo

Cyber-enabled power system places higher requirements on the reliability of communication infrastructure. This paper proposes an approach to calculate reliability of distribution networks in the presence of communication media. Communication failure is incorporated into sequential Monte Carlo simulation using a uniform probability distribution function. A straightforward matrix representation is developed to analyze the impact of fault on each load point. Several scenarios are discussed to illustrate the impact of potential communication failures. For each scenario energy not supplied is calculated for Bus 2 of RBTS. The results show the necessity of evolving well-established reliability calculation methods.

Loss allocation control in power distribution system reconfiguration in the presence of distributed generators

In a deregulated power distribution system with distributed generation, end users should be allocated the appropriate cost of energy transactions for fair and effective operation. One of the common practices is to allocate the cost of power losses to distributed generators (DGs) and consumers based on their effective share. According to the network configuration, DGs and consumers could have positive or negative impacts on a systems overall loss. This paper addresses the effect of power distribution system reconfiguration on each users share of loss. The overall system loss and maximum allocated loss are considered in the two competing objectives to be minimized. The branch current decomposition method is used to calculate the allocated losses to each bus. The group search optimizer (GSO), a swarm intelligence optimization method, is used to find the best solution. Using weighted factors, the priorities of decision-makers are applied to the optimization problem. A 33-bus distribution system is used for which the best possible configuration is found.

Component reliability evaluation in the presence of smart monitoring

Smart sensors and monitoring technologies are beginning to penetrate different levels of the power system. In a smart grid scenario, the operational condition of components needs to be reported to the control center, in order to improve the remedial action for an ailing component. This will significantly reduce the component failure rate and improve reliability of the entire system. This paper proposes a Markov model to quantify the reliability of a component in the presence of smart monitoring. A mathematical formulation based on the absorbing state concept is used to calculate the failure rate of the monitored component. A numerical analysis is performed to evaluate the impact of some parameters on the failure rate of the monitored component.

A stochastic modeling of aggregated vehicle-to-grid for reliability assessment of distribution network

This paper proposes a stochastic modeling of aggregated vehicle-to-grid (V2G) based on sequential Monte Carlo simulation for reliability evaluation of distribution network. Uncertainties of electric vehicle (EV) travel information including parking lot arrival time, travelled distance and parking lot departure time are incorporated into reliability evaluation using appropriate probability distribution functions. This model aids decision maker during planning phase to better estimate the impact of V2G on system reliability. The proposed model is used for optimal placement of a parking lot in an official center distribution network with the objective of reducing the expected energy not served.

Life time analysis of distribution transformer using experimental design

This paper presents a 24 factorial design to analyze the joint effect of loading, cooling characteristics, ambient temperature, and Oil Time Constant (OTC) on transformer Loss of Life (LOL). Transformer LOL is calculated for 16 combinations of factor levels. Residential load profile obtained from a utility is used to precisely model the loading factor. Design-Expert® Software Version 9 is used to statistically analyze the joint effect of factors. Results show the significance and contribution of factors and their interactions to distribution transformer loss of life.

Performance characterization of a solar panel: A case study

This paper used the design of experiment concepts to develop a model that estimates the output power of a solar panel under certain experimental conditions and factors. This study will help in deciding the optimal placement of a solar panel to get the maximum output power based on the most influencing studied factors.